Current status of hepatocellular carcinoma detection: screening strategies and novel biomarkers.

Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality worldwide. Delayed diagnosis is a major factor responsible for the poor prognosis of HCC. Several advances have been made in the field of liver imaging with the use of novel imaging contrasts, improving current imaging techniques with contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI), introduction of new technologies such as contrast liver ultrasound, and development of novel biomarkers with the goal of early detection of HCC and improving outcomes of patients with HCC. This review focuses on current surveillance strategies and development of biomarkers with the goal of early detection of HCC

Quark Mass Matrices with Four and Five Texture Zeroes, and the CKM Matrix, in terms of Mass Eigenvalues

Using the triangular matrix techniques of Kuo et al and Chiu et al for the four and five texture zero cases, with vanishing (11) elements for U and D matrices, it is shown, from the general eigenvalue equations and hierarchy conditions, that the quark mass matrices, and the CKM matrix can be expressed (except for the phases) entirely in terms of quark masses. The matrix structures are then quite simple and transparent. We confirm their results for the five texture zero case but find, upon closer examination of all the CKM elements which our results provide, that six of their nine patterns for the four texture zero case are not compatible with experiments. In total, only one five-texture zero and three four-texture zero patterns are allowed.Comment: 15 pages, 3 table

On the Evolution of the Neutrino State inside the Sun

We reexamine the conventional physical description of the neutrino evolution inside the Sun. We point out that the traditional resonance condition has physical meaning only in the limit of small values of the neutrino mixing angle, theta<<1. For large values of theta, the resonance condition specifies neither the point of the maximal violation of adiabaticity in the nonadiabatic case, nor the point where the flavor conversion occurs at the maximal rate in the adiabatic case. The corresponding correct conditions, valid for all values of theta including theta>pi/4, are presented. An adiabaticity condition valid for all values of theta is also described. The results of accurate numerical computations of the level jumping probability in the Sun are presented. These calculations cover a wide range of Delta m^2, from the vacuum oscillation region to the region where the standard exponential approximation is good. A convenient empirical parametrization of these results in terms of elementary functions is given. The matter effects in the so-called "quasi-vacuum oscillation regime" are discussed. Finally, it is shown how the known analytical results for the exponential, 1/x, and linear matter distributions can be simply obtained from the formula for the hyperbolic tangent profile. An explicit formula for the jumping probability for the distribution N_e ~ (coth(x/l) +- 1) is obtained.Comment: 34 pages, 8 figure

Artificial intelligence in fracture detection: a systematic review and meta-analysis

Background: Patients with fractures are a common emergency presentation and may be misdiagnosed at radiologic imaging. An increasing number of studies apply artificial intelligence (AI) techniques to fracture detection as an adjunct to clinician diagnosis. Purpose: To perform a systematic review and meta-analysis comparing the diagnostic performance in fracture detection between AI and clinicians in peer-reviewed publications and the gray literature (ie, articles published on preprint repositories). Materials and Methods: A search of multiple electronic databases between January 2018 and July 2020 (updated June 2021) was performed that included any primary research studies that developed and/or validated AI for the purposes of fracture detection at any imaging modality and excluded studies that evaluated image segmentation algorithms. Meta-analysis with a hierarchical model to calculate pooled sensitivity and specificity was used. Risk of bias was assessed by using a modified Prediction Model Study Risk of Bias Assessment Tool, or PROBAST, checklist. Results: Included for analysis were 42 studies, with 115 contingency tables extracted from 32 studies (55061 images). Thirty-seven studies identified fractures on radiographs and five studies identified fractures on CT images. For internal validation test sets, the pooled sensitivity was 92% (95% CI: 88, 93) for AI and 91% (95% CI: 85, 95) for clinicians, and the pooled specificity was 91% (95% CI: 88, 93) for AI and 92% (95% CI: 89, 92) for clinicians. For external validation test sets, the pooled sensitivity was 91% (95% CI: 84, 95) for AI and 94% (95% CI: 90, 96) for clinicians, and the pooled specificity was 91% (95% CI: 81, 95) for AI and 94% (95% CI: 91, 95) for clinicians. There were no statistically significant differences between clinician and AI performance. There were 22 of 42 (52%) studies that were judged to have high risk of bias. Meta-regression identified multiple sources of heterogeneity in the data, including risk of bias and fracture type. Conclusion: Artificial intelligence (AI) and clinicians had comparable reported diagnostic performance in fracture detection, suggesting that AI technology holds promise as a diagnostic adjunct in future clinical practice

Typical and Atypical Antipsychotic Drugs Increase Extracellular Histamine Levels in the Rat Medial Prefrontal Cortex: Contribution of Histamine H1 Receptor Blockade

Atypical antipsychotics such as clozapine and olanzapine have been shown to enhance histamine turnover and this effect has been hypothesized to contribute to their improved therapeutic profile compared to typical antipsychotics. In the present study, we examined the effects of antipsychotic drugs on histamine (HA) efflux in the mPFC of the rat by means of in vivo microdialysis and sought to differentiate the receptor mechanisms which underlie such effects. Olanzapine and clozapine increased mPFC HA efflux in a dose related manner. Increased HA efflux was also observed after quetiapine, chlorpromazine, and perphenazine treatment. We found no effect of the selective 5-HT2A antagonist MDL100907, 5-HT2c antagonist SB242084, or the 5-HT6 antagonist Ro 04-6790 on mPFC HA efflux. HA efflux was increased following treatment with selective H1 receptor antagonists pyrilamine, diphenhydramine, and triprolidine, the H3 receptor antagonist ciproxifan and the mixed 5-HT2A/H1 receptor antagonist ketanserin. The potential novel antipsychotic drug FMPD, which has a lower affinity at H1 receptors than olanzapine, did not affect HA efflux. Similarly, other antipsychotics with lower H1 receptor affinity (risperidone, aripiprazole, and haloperidol) were also without effect on HA efflux. Finally, HA efflux after antipsychotic treatment was significantly correlated with affinity at H1 receptors whereas nine other receptors, including 5-HT2A, were not. These results demonstrate that both typical and atypical antipsychotics increase mPFC histamine efflux and this effect may be mediated via antagonism of histamine H1 receptors

Stakeholder perspectives towards diagnostic artificial intelligence: a co-produced qualitative evidence synthesis

Background: Diagnosis is a cornerstone of medical practice. Worldwide, there is increased demand for diagnostic services, exacerbating workforce shortages. Artificial intelligence (AI) technologies may improve diagnostic efficiency, accuracy, and access. Understanding stakeholder perspectives is key to informing implementation of complex interventions. We systematically reviewed the literature on stakeholder perspectives on diagnostic AI, including all English-language peer-reviewed primary qualitative or mixed-methods research. Methods: We searched PubMed, Ovid MEDLINE/Embase, Scopus, CINAHL and Web of Science (22/2/2023 and updated 8/2/2024). The Critical Appraisal Skills Programme Checklist informed critical appraisal. We used a ‘best-fit’ framework approach for analysis, using the Non-adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework. This study was pre-registered (PROSPERO CRD42022313782). Findings: We screened 16,577 articles and included 44. 689 participants were interviewed, and 402 participated in focus groups. Four stakeholder groups were described: patients, clinicians, researchers and healthcare leaders. We found an under-representation of patients, researchers and leaders across articles. We summarise the differences and relationships between each group in a conceptual model, hinging on the establishment of trust, engagement and collaboration. We present a modification of the NASSS framework, tailored to diagnostic AI. Interpretation: We provide guidance for future research and implementation of diagnostic AI, highlighting the importance of representing all stakeholder groups. We suggest that implementation strategies consider how any proposed software fits within the extended NASSS-AI framework, and how stakeholder priorities and concerns have been addressed

BICEP2 / Keck Array V: Measurements of B-mode Polarization at Degree Angular Scales and 150 GHz by the Keck Array

The Keck Array is a system of cosmic microwave background (CMB) polarimeters, each similar to the BICEP2 experiment. In this paper we report results from the 2012 and 2013 observing seasons, during which the Keck Array consisted of five receivers all operating in the same (150 GHz) frequency band and observing field as BICEP2. We again find an excess of B-mode power over the lensed-$\Lambda$CDM expectation of $> 5 \sigma$ in the range $30 < \ell < 150$ and confirm that this is not due to systematics using jackknife tests and simulations based on detailed calibration measurements. In map difference and spectral difference tests these new data are shown to be consistent with BICEP2. Finally, we combine the maps from the two experiments to produce final Q and U maps which have a depth of 57 nK deg (3.4 $\mu$K arcmin) over an effective area of 400 deg$^2$ for an equivalent survey weight of 250,000 $\mu$K$^{-2}$. The final BB band powers have noise uncertainty a factor of 2.3 times better than the previous results, and a significance of detection of excess power of $> 6\sigma$.Comment: 13 pages, 9 figure